Atomfair Brainwave Hub: SciBase II / Artificial Intelligence and Machine Learning / AI-driven climate and disaster modeling

AI-driven climate and disaster modeling

Showing 1-12 of 295 articles

Integrating paleoclimatology with machine learning to predict regional hydroclimate extremes

For 2040 climate migration scenarios with predictive AI modeling

Across magma chamber dynamics with distributed fiber-optic sensing

Employing retrieval-augmented generation to map Cold War-era nuclear fallout dispersal patterns

Using AI-driven wildfire prediction models to optimize evacuation routes in real-time

Across magma chamber dynamics during volcanic unrest periods

Planning for next glacial period through geoengineered climate stabilization

Planning for next glacial period using advanced climate modeling techniques

Projecting 2030 infrastructure needs with climate-resilient urban planning strategies

For earthquake prediction using machine learning on slow-slip event precursors

Predicting earthquake aftershocks via machine learning analysis of seismic waveform patterns

Marrying ethology with swarm robotics for adaptive disaster response systems